DocumentCode :
123499
Title :
Research on educational data mining of digital learning process for elementary school
Author :
Fang Hai-guang ; Hou Wei-feng ; Wang Xiao-chun ; Chu Yun-hai
Author_Institution :
Dept. of Educ. Technol., Capital Normal Univ., Beijing, China
fYear :
2014
fDate :
22-24 Aug. 2014
Firstpage :
849
Lastpage :
854
Abstract :
Personalized learning is an important goal for the future education reform and innovation. Nowadays, analysis of the classroom learning process for elementary school relies on the teacher´s experience because of one-way learning information transfer mode and without enough tracking. Multidimensional information interaction data cannot be received as real-time processing and analyzed in the process of learning for elementary school, which leads to lacking of practical basis for personalized learning. This study is focused on using PAD for teaching and studying in digital classroom under the network environment, based on the learning process information exchanged between teachers and students, so as to construct the PADClass model. Based on the model, educational data can be collected and descripted in the learning process, and it can be gotten the teaching strategies and suggestions from educational data mining and analysis according to the domain knowledge. Teachers using these data and analysis results can control teaching process and teaching reflection in real time, so as to improve the classroom teaching quality. Students using these data and the results of analysis, can discover the problems of learning themselves immediately, and can improve their learning quality.
Keywords :
computer aided instruction; data mining; information management; teaching; PADClass model; classroom learning process; classroom teaching quality; digital classroom; digital learning process; educational data mining; elementary school; information exchange; learning quality; multidimensional information interaction; one-way learning information transfer mode; personalized learning; teaching process; teaching reflection; Analytical models; Computers; Data mining; Educational institutions; Indexes; Irrigation; Visualization; Data analysis; Digital classroom; Educational data mining; Learning process; PAD;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Education (ICCSE), 2014 9th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4799-2949-8
Type :
conf
DOI :
10.1109/ICCSE.2014.6926582
Filename :
6926582
Link To Document :
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